Derailing healthy choices: an audit of vending machines at train stations in NSW

RIS ID

57140

Publication Details

Kelly, B., Flood, V. M., Bicego, C. & Yeatman, H. (2012). Derailing healthy choices: an audit of vending machines at train stations in NSW. Health Promotion Journal of Australia, 23 (1), 73-75.

Abstract

Introduction Vending machines epitomise the high availability and convenience of food and beverages in Western society and are available in many settings, including schools,1,2 workplaces3 and health care facilities.4 In some locations, the availability of alternative food and beverages outside of vending machines may be limited.5 In 2006 there were 3.5 million vending machines in the US for cold beverages alone.6 While no Australian industry data are available, observational evidence indicates that these machines are ubiquitous and stock predominantly unhealthy drinks and snacks. Such persistent exposure to unhealthy foods and beverages can influence consumption by providing increased opportunities for the purchase of unhealthy items, and by providing visual cues to prompt consumers to eat and drink.5 Train stations provide opportunities to purchase food and beverages, and many consumers are exposed to these venues daily, on their commute to and from work. One in five Australian adults used public transport as their main mode of travel to work/study in 2006, although this was higher in Sydney (26%).7 The relatively closed environment of train stations means that commuters are limited to the products available on site or in the immediate vicinity. As such, these venues may cumulatively contribute to excess energy consumption if the foods and beverages offered are energy dense. This survey aimed to determine the nature of food and beverages available to commuters through vending machines on train platforms across the Greater Sydney Metropolitan area. This information will be useful to guide future interventions to modify food environments in these settings. Methods Sampling 100 train stations (from a possible 291) were selected across the Sydney Greater Metropolitan region through stratified random sampling. Stations were stratified by socioeconomic status (SES) according to the Australian Bureau of Statistics Socio-Economic Indexes for Areas (SEIFA) Index of Relative Socio-economic Advantage and Disadvantage, based on postcode.8 SEIFA scores were classified as high (>1,100), medium (1,000-1,100) and low (

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